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Spatial Distribution Characteristics of Biomass and Carbon Storage in Forest Vegetation in Chongqing Based on RS and GIS

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Spatial Distribution Characteristics of Biomass and Carbon Storage in Forest Vegetation in Chongqing Based on RS and GIS Nature Environment and Pollution Technology ISSN: 0972-6268 Vol. 15 No. 4 pp. 1381-1388 2016 An International Quarterly Scientific Journal Original Research Paper Spatial Distribution Characteristics of Biomass and Carbon Storage in Forest Vegetation in Chongqing Based on RS and GIS Qiannan Liu*(**), Zhiyun Ouyang***†, Ainong Li* and Weihua Xu*** *Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu Sichuan, 610041, China **University of Chinese Academy of Sciences, Beijing 100049, China ***Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China †Corresponding author: Zhiyun Ouyang ABSTRACT Nat. Env. & Poll. Tech. Website: www.neptjournal.com Research on the spatial distribution characteristics of carbon storage in forest vegetation not only facilitates the study of carbon sink and ecological compensation of the forest ecosystem, but also Received: 15-12-2015 provides basic data for recovering and reconstructing the forest ecosystem and increasing the Accepted: 28-01-2016 carbon sink. In this study, remote sensing images of Landsat TM (August) in 2011 and a large amount Key Words: of actual surveyed data of the sample plots were used as the main and supplementary data sources, Biomass respectively. Chongqing was selected as the study site to quantitatively estimate the biomass, carbon Forest vegetation storage, and carbon density of forest vegetation based on the biomass-remote sensing (RS) geoscientific Carbon storage data regression model with the aid of RS and GIS techniques. With the spatial analysis function of Vegetation index ArcGIS, factors affecting the geographic distribution of biomass were investigated from a macroscopic perspective, and the geographical distribution pattern characteristics of biomass in the study area were quantitatively discussed. Results showed that the total aboveground biomass of Chongqing is 2.83×108 t, and that of the forest ecosystem is 1.39×108 t. Biomass was mainly distributed in northeast and southeast Chongqing, and the overall distribution pattern was high in the east and low in the west. Forest vegetation and biomass were mainly distributed in mid-high altitudes with steep slopes. Despite the results of this biomass and carbon storage study using RS in Chongqing, further research based on the carbon cycle is needed. INTRODUCTION environmental science (Zhang et al. 2010). Qualitative stud- ies on biomass and carbon storage in the forest ecosystem in As the main body of the terrestrial ecosystem, forests store China have been conducted, but most of them focused on 72% to 98% of the terrestrial ecosystem’s organic carbon either the nationwide or local scale (Fang et al. 2001, Wang (Wang et al. 2001). The fixed carbon storage in forest veg- et al. 2004, Zhao & Zhou 2004). Research on carbon stor- etation accounts for 82.15% of the total carbon fixation of age and carbon sink function of the middle scale or regional terrestrial vegetation (Sabine et al. 2004). A total of 85% of forest ecosystem is relatively weak (Wang et al. 2010), and terrestrial biomass is concentrated on the forest vegetation studies on forest biomass, carbon storage, and carbon sink (Fang et al. 2002), which shows higher productivity than other function in the southwestern forest region on the middle terrestrial ecosystems (Turneret et al. 1995). Thus, the scale are lacking. Using Chongqing as the study area is biomass and productivity of the forest exert very important particularly rare. effects on global climate change and material cycling (Cramer et al. 1999, Field et al. 1999), maintain the re- The forest vegetation in Chongqing and Sichuan is the gional ecological environment, and balance carbon distribu- main part of the southwestern forest region in China. Lo- tion in the world (Liu et al. 2000, Dixon et al. 1999, Xu et cated on the east edge of the Qinghai-Tibet Plateau, which al. 2012). The forest acts as the source, storehouse, and sink is considered the world’s third pole, the study location is a in the global circulation of carbon (Fu et al. 2005). Forest sensitive response area to global climate change (Zhang et carbon storage is taken as the basic parameter that reflects al. 1995). In addition, the forest vegetation is mostly dis- the function of the forest ecosystem (Ge et al. 2013), and it is tributed in the upper reaches of the Yangtze River, making calculated by accurately estimating vegetation biomass (ICPC it an important site for water resource conservation and pro- 2004, ICPC 2006). In addition to forest vegetation, the rela- tection while maintaining the ecological balance in the river tionship between regional forest vegetation and global cli- (Huang et al. 2008). Chongqing became a municipality di- mate change is a hot spot in the research of ecology and rectly under the Central Government, and since the imple- 1382 Qiannan Liu et al. mentation of major forest projects, such as the Yangtze River occurs because of numerous mountains, high slopes, and grebe belt, green gills, and clear waters, the forest area has uneven distribution of rainfall in different seasons (Zhang been increasing continuously, making the forest vegetation et al. 2004). an important contributor to carbon sink and carbon balance. Remote sensing data processing: This study is based on However, studies based on the biomass and carbon sink ca- 1:50000 topographic map geographical data. The remote pacity of the forest vegetation are rare, and research on fu- sensing software ENVI 4.8 adopts the quadratic polynomial ture carbon sink potential after conducting forest projects is and adjacent interpolation method to complete the geomet- lacking. The present study used a biomass-remote sensing ric correction of Landsat TM remote sensing data shadow in (RS) geoscientific data multiple regression model to estab- 2011 and control the correction error within 1 pixel. The lish the RS biomass model of the forest vegetation, with projection way is the UTM (Zone48N), and the coordinate Landsat TM in Chonqing (2011) as the main data source and system is WGS84. FLASSH module of the software was used a large amount of field survey and forest inventory data as to complete the atmospheric correction of remote sensing the basis. Based on the biomass estimation of the forest veg- image and eliminate the influence of atmospheric scatter- etation and the ArcGIS spatial analysis module, the proposed ing on the image radiation distortion. Terrain correction of model uses DEM data, land use situation, and carbon con- the remote sensing image based on DEM was completed to tent of forest vegetation to quantitatively analyse the spa- eliminate the influence of mountain shadow on the forest tial distribution properties of forest vegetation biomass un- vegetation and conduct mask cutting processing on the der different topographic features. The factors affecting the image according to the administrative boundary of the study geographical distribution of biomass, as well as the geo- area. graphical distribution characteristics of carbon storage in the study area, were also explored in a macroscopic per- The overall land classification systems, characteristics spective. The research results have important theoretical of Landsat TM data, and actual land use situation in the basis and practical significance in evaluating the carbon study area complete the field sampling survey on the test sink function of forest vegetation, calculating the green GDP area. After obtaining a large amount of field-surveyed sam- (Gross Domestic Product), and establishing the ecological ples, the multi-step classification method was conducted to effect compensation mechanism of the forest carbon. This complete the classification processing of the remote sensing study also provides a scientific decision-making service and images by the classification model established in ERDAS technical reference for the implementation of CDM (Clean IMAGE 9.3. Land use in Chongqing is classified into seven Development Mechanism) afforestation and other relevant grades, namely, forest, shrub, grassland, wetland, farmland, carbon sink projects in the regions of Chongqing in the town, and bare land. The study adopts random sampling to future. complete the precision verification of the classification re- sult. The Kappa coefficient is 0.893, which is higher than the RESEARCH AREA AND RESEARCH METHOD minimum allowed discriminant precision requirement of 0.7. In addition, the Kappa coefficient completes the correction Introduction of the research area: Chongqing City (E: and topology processing of the final classification results based 105°17'-110°11’; N: 28°10'-32°13') is bordered by Hubei on ArcGIS 9.3 to generate the thematic map of land use Province and Hunan Province to the east, Guizhou Province distribution. to the south, and Sichuan Province to the west and north. Its northeast is bordered to Shan’anxi Province. It is an eco- The Model module of ERDAS IMAGE 9.3 was used to nomic center in the upper Yangtze River, an important in- complete the quantitative extraction of ratio vegetation in- dustrial town in the southwest, a hub of land and water trans- dex (RVI), normalized difference vegetation index (NDVI), portation, and an important ecological barrier of the Yang- atmospheric resistance vegetation index (ARVI), modified tze River basin. It covers an area of 82400 km2, with moun- soil atmosphere resistance vegetation index (MSAVI), and tains accounting for 75.8% and hills for 18.2% of the total enhanced vegetation
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